Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

BACKGROUND: Pre-transplant exposure to immune checkpoint inhibitors (ICIs) significantly increases the risk of allograft rejection after liver transplantation (LT); however, whether ICI-related rejection leads to increased graft loss remains controversial. Therefore, this study aimed to investigate the association between ICI-related allograft rejection and perioperative graft loss. METHODS: This was a retrospective analysis of adult liver transplant recipients with early biopsy-proven T-cell-mediated rejection (TCMR) at Liver Transplantation Center of Sun Yat-sen Memorial Hospital from June 2019 to September 2024. The pathological features, clinical characteristics, and perioperative graft survival were analyzed. RESULTS: Twenty-eight patients who underwent early TCMR between June 2019 and September 2024 were included. Based on pre-LT ICI exposure, recipients were categorized into ICI-related TCMR (irTCMR, n = 12) and conventional TCMR (cTCMR, n = 16) groups. Recipients with irTCMR had a higher median Banff rejection activity index (RAI) (6 vs . 5, P = 0.012) and more aggressive tissue damage and inflammation. Recipients with irTCMR showed higher proportion of treatment resistance, achieving a complete resolution rate of only 8/12 compared to 16/16 for cTCMR. Graft loss occurred in 5/12 of irTCMR recipients within 90 days after LT, with no graft loss in cTCMRs recipients. Cox analysis demonstrated that irTCMR with an ICI washout period of <30 days was an independent risk factor for perioperative graft loss (hazard ratio [HR], 6.540; 95% confidence interval [CI], 1.067-40.067, P = 0.042). CONCLUSION IrTCMR is associated with severe pathological features, increased resistance to treatment, and higher graft loss in adult liver transplant recipients.
Humans ; Liver Transplantation/adverse effects* ; Male ; Female ; Middle Aged ; Retrospective Studies ; Graft Rejection/immunology* ; Immune Checkpoint Inhibitors/therapeutic use* ; Adult ; T-Lymphocytes/drug effects* ; Graft Survival/immunology* ; Aged

The study aims to examine the effects and potential mechanisms of disulfiram (DSF) on cardiac hypertrophic injury, focusing on the role of transforming growth factor-β-activated kinase 1 (TAK1)-mediated pan-apoptosis (PANoptosis). H9C2 cardiomyocytes were treated with angiotensin II (Ang II, 1 µmol/L) to establish an in vitro model of myocardial hypertrophy. DSF (40 µmol/L) was used to treat cardiomyocyte hypertrophic injury models, either along or in combination with the TAK1 inhibitor, 5z-7-oxozeaenol (5z-7, 0.1 µmol/L). We assessed cell damage using propidium iodide (PI) staining, measured cell viability with CCK8 assay, quantified inflammatory factor levels in cell culture media via ELISA, detected TAK1 and RIPK1 binding rates using immunoprecipitation, and analyzed the protein expression levels of key proteins in the TAK1-mediated PANoptosis pathway using Western blot. In addition, the surface area of cardiomyocytes was measured with Phalloidin staining. The results showed that Ang II significantly reduced the cellular viability of H9C2 cardiomyocytes and the binding rate of TAK1 and RIPK1, significantly increased the surface area of H9C2 cardiomyocytes, PI staining positive rate, levels of inflammatory factors [interleukin-1β (IL-1β), IL-18, and tumor necrosis factor α (TNF-α)] in cell culture media and p-TAK1/TAK1 ratio, and significantly up-regulated key proteins in the PANoptosis pathway [pyroptosis-related proteins NLRP3, Caspase-1 (p20), and GSDMD-N (p30), apoptosis-related proteins Caspase-3 (p17), Caspase-7 (p20), and Caspase-8 (p18), as well as necroptosis-related proteins p-MLKL, RIPK1, and RIPK3]. DSF significantly reversed the above changes induced by Ang II. Both 5z-7 and exogenous IL-1β weakened these cardioprotective effects of DSF. These results suggest that DSF may alleviate cardiac hypertrophic injury by inhibiting TAK1-mediated PANoptosis.
Animals ; MAP Kinase Kinase Kinases/physiology* ; Rats ; Myocytes, Cardiac/pathology* ; Disulfiram/pharmacology* ; Cardiomegaly ; Apoptosis/drug effects* ; Cell Line ; Angiotensin II ; Necroptosis/drug effects* ; Interleukin-1beta/metabolism* ; Receptor-Interacting Protein Serine-Threonine Kinases/metabolism* ; Lactones ; Resorcinols ; Zearalenone/administration & dosage*

Atrial fibrillation (AF) is the most common arrhythmia in clinical practice. It has a high prevalence and poor prognosis. The application of antiarrhythmic drugs and even surgery cannot completely treat the disease, and there are many sequelae. AF can be classified into the category of "palpitation" in Chinese medicine according to its symptoms. Acupuncture has a significant effect on AF. The authors find that an important mechanism of acupuncture in AF treatment is to regulate the cardiac vagus nerve. Therefore, this article intends to review the distribution and function of vagus nerve in the heart, the application and the regulatroy effect for the treatment of AF.
Atrial Fibrillation/physiopathology* ; Humans ; Acupuncture Therapy ; Vagus Nerve/physiology* ; Animals

Traditional Chinese medicine (TCM) is a well-accepted therapy for atopic dermatitis (AD). However, there are currently no evidence-based guidelines integrating TCM and Western medicine for the treatment of AD, limiting the clinical application of such combined approaches. Therefore, the China Association of Chinese Medicine initiated the development of the current guideline, focusing on key issues related to the use of TCM in the treatment of AD. This guideline was developed in accordance with the principles of the guideline formulation manual published by the World Health Organization. A comprehensive review of the literature on the combined use of TCM and Western medicine to treat AD was conducted. The findings were extensively discussed by experts in dermatology and pharmacy with expertise in both TCM and Western medicine. This guideline comprises 23 recommendations across seven major areas, including TCM syndrome differentiation and classification of AD, principles and application scenarios of TCM combined with Western medicine for treating AD, outcome indicators for evaluating clinical efficacy of AD treatment, integration of TCM pattern classification and Western medicine across disease stages, daily management of AD, the use of internal TCM therapies and proprietary Chinese medicines, and TCM external treatments. Please cite this article as: Du XR, Wu MY, Tao MC, Lin Y, Gu CY, Wu MF, Cao Y, Chen DC, Li W, Wang HW, Wang Y, Wang Y, Lu HZ, Liu X, Su XF, Li FL. Clinical practice guidelines for the diagnosis and treatment of atopic dermatitis with integrative traditional Chinese and Western medicine. J Integr Med. 2025; 23(6):641-653.
Dermatitis, Atopic/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Integrative Medicine ; Drugs, Chinese Herbal/therapeutic use* ; Practice Guidelines as Topic

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Objective To investigate the satisfaction of clinical trial service quality of hospitals in Shanghai for clinical research associate(CRA),so as to provide reference for improving the quality of clinical trial service.Methods From Oct to Nov 2023,CRAs were surveyed using the revised SERVQUAL(service quality)scale.The questionnaire included 29 items in 5 dimensions of assurance,reliability,tangibility,responsiveness and empathy.Based on the modified importance-performance analysis(IPA)analysis,it was figured out which item was in the improvement area.Results A total of 163 CRAs from 10 companies were surveyed,and 160 valid questionnaires were collected.According to the revised IPA,6,2,1,2 and 2 items of the dimensions of assurance,reliability,tangibility,responsiveness and empathy fell into the improvement area,respectively.Conclusion CRAs surveyed may not be satisfied with the clinical trial service of Shanghai hospitals.We need to propose optimization strategies to improve the quality of clinical trial service from the aspects of standardization awareness,review mode,process acquisition,response and management system flexibility.

Objective To explore the effect of a R language-based autoregressive integrated moving average(ARIMA)model for predicting the consumption of medical consumables.Methods The monthly consumption data of a certain type of pre-filled flush syringe from July 2018 to June 2023 was selected as the sample data,which underwent smoothness test and difference operation with R language.An ARIMA model was established and the optimal model was determined according to the Akaike and Bayesian information criteria.The corresponding data of the third quarter of 2023 was used as the validation set to predict the consumption,and the prediction result was compared with the actual values to evaluate the prediction effect of the ARIMA model.Results The ARIMA model with the best fitting was ARIMA(0,1,1)(1,0,0)12,all the predicted data were within 95％confidence interval,and its mean absolute percentage error MAPE was 9.92％.P-value proved to be higher than 0.05 when the residual series were tested using the Ljung-Box statistics,which meant the prediction result was satisfactory.Conclusion The R language-based ARIMA model behaves well in predicting the consumption of medical consumables,and provides references for demand planning,budgeting,purchasing and management of medical consumables.[Chinese Medical Equipment Journal,2024,45(10):84-87]